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Record W4399660537 · doi:10.32920/26042728.v1

Forgotten Not Lost: Rediscovering the Life and Work of Minna Keene (1859-1943) at the Image Centre

2024· preprint· en· W4399660537 on OpenAlexaffabout
Mina Markovic

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStudioBiographyHistoryArt historyVisual artsArt

Abstract

fetched live from OpenAlex

During her lifetime, Minna Keene (1859-1943) was a celebrated pictorialist and studio photographer, and one of the first women admitted as a fellow to the Royal Photographic Society (RPS). Keene maintained several photographic studios trans-nationally, including in South Africa between 1903 and 1913, and Montreal, Toronto and Oakville from 1913 until 1943. Yet, after her death, Keene’s work was forgotten. Few scholars studied Keene’s career and her photographs disappeared from both public and photo-historical view. In 2021, The Image Centre in Toronto announced the acquisition of the Minna Keene and Violet Keene Perinchief Collection. Using this never-before-seen material, this thesis constructs the first comprehensive biography on Keene, including a chronology detailing her many achievements throughout her career, and analyzes the scope and content of a collection spanning approximately 3,864 objects attributed to Keene. This approach lays the foundation for future researchers to examine Keene’s diverse oeuvre at The Image Centre.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0270.023
Scholarly communication0.0100.008
Open science0.0010.009
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.249
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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